Detection of video segments is used to recognize known video segments and take subsequent video processing steps. In one example, specific advertisements or video scenes are detected in a video stream and substituted or deleted from the video stream. In other applications it is desirable to recognize certain scenes for other purposes such as video indexing or the creation of other metadata or other reference material attached to that particular video scene. In all of these examples it is necessary to be able to recognize a known video segment.
Methods have been developed which can be used to detect known video sequences. These methods include recognition of certain characteristics associated with scene changes or certain video segments as well as the comparison of video segments with fingerprints of those video segments. In the fingerprinting technique, the known video segments are characterized and the incoming video stream is compared with the characterizations to determine if a known video sequence is in fact present at that time.
One technique for recognizing video segments is to create a color coherence vector (CCV) or a low-res image (e.g., of size 8 by 8 pixels) representation of a known video sequence and compare the CCV or low-res image fingerprint against the color coherence vectors or low-res images of incoming video streams. Other techniques can be used to compare the incoming video to stored fingerprints but all of the known presently used techniques are based on operations performed in the uncompressed domain. This requires that the video be completely decompressed in order to calculate the specific parameters of the fingerprint and perform a comparison. Even in the instances in which there is a partial decompression, specific algorithms performed on the decompressed stream need to be performed to compare the incoming video stream with the fingerprint. It is desirable to have a method and system of detecting video sequences in compressed digital video streams prior to their decompression.